Harnessing data for development, translating insights for social innovation

Mar 23

Research Dive Review: Statistics for the SDGs

By Dikara Alkarisya and Zakiya Pramestri

From 12th to 15th March, Pulse Lab Jakarta hosted its third research dive, bringing together statisticians from across Indonesia to analyse data from the Millennium Development Goals in order to support the implementation and monitoring of the Sustainable Development Goals (SDGs). Below we share our impressions from the event and the next steps for the teams.

Working Against the Clock

We were honoured to host 15 researchers and five national statisticians from across Indonesia, along with five advisors, for the research dive. Given the 15-years of national and sub-national level MDG data, the participants were grouped into five research teams:

Data Disaggregation: to propose a set of statistical methods to disaggregate Indonesian data by gender, age, and at the subnational level

During the event, the teams engaged in lively debate about the best-fit statistical methods and worked against the clock to develop research methods and insights under the five topics.

Challenges and Opportunities around Data

The implementation of the SDGs has brought about some challenges especially concerning data collection, as the SDGs include 169 targets and 230 indicators, but also some opportunities to use new data sources in addressing data gaps.

In kicking off the event, Dr. Ali Said, the Head of Sub-directorate for Statistical Indicators at the National Bureau of Statistics (BPS), highlighted the big picture: that after remapping the SDGs indicators, 31 percent of global indicators are not yet tracked in Indonesia.

He conveyed that several initiatives have been undertaken by BPS, for instance, by modifying existing surveys, developing new surveys, and exploring the possibility of using big data and other data sources. But since some indicators still cannot be covered by conventional methods, BPS is looking for more sophisticated approaches, statistical models and analysis to fill the existing gap of data availability, accessibility, and reliability.

Diving into MDG Datasets to inform the SDGs

Spanning the event, the researchers analysed publicly available data on the MDGs across 34 provinces in Indonesia. Despite the narrow time limit, all the teams developed relevant statistical methods for the tasks at hand.

The first group explored the correlations between MDG indicators, and also clustered the provinces based on performance. For example, they discovered a positive correlation between extreme poverty & hunger and the incidence of tuberculosis. The second group explored the role of education and health in driving poverty. They found that literacy rates and sustainable access to basic sanitation have the greatest statistical impact on poverty.

The third group developed proxies for currently unavailable SDG indicators, for instance, the proportion of population using safely managed drinking water services, by using measurements including the proportion of population below poverty line, the proportion of population consuming clean water, and the proportion of population with access to improved sanitation. The fourth group proposed a framework to ensure the quality of data, by using proxies and validating outliers. The last group managed to disaggregate national level data to the provincial level, by applying a set of numerical methods, including simple proportion, neighborhood-based, and correlation-based methods.

All of these statistical approaches could be useful for policy makers as well as domain experts during the implementation of the SDGs, in terms of filling data gaps and also understanding the relationships among indicators.

A Workshop within a Workshop

The five advisors shared their research experiences on statistics for evidence-based policy-making. There were around 30 extra participants for these presentations drawn from various organisations working on SDGs-related issues as well as from the field of statistics.

The five presentations included Dr. Ali Said, M.A from BPS, who opened the presentations by explaining “Domain Challenges and Implications in the Statistics for SDGs.” Dr. Danardono from Universitas Gajah Mada, explained his research on “Modeling Mortality by Combining Formal Mortality Reports and Social Media Information.” Dr. Bagus Sartono from Institut Pertanian Bogor described his “Study of Economic Leading Indicators and Financial Inclusion.” Dr. Suhartono from Institut Teknologi Sepuluh Nopember highlighted the “Intervention Analysis: Statistical Model for Evaluating the Impact of Policy and Disaster.” The last presentation was presented by Dr. Tiodora Hadumaon Siagian from Sekolah Tinggi Ilmu Statistik (STIS) who talked about “Statistics Application for Supporting Disaster Risk Reduction in Indonesia.” The advisors’ slides are accessible at this link.

Feedback from the Participants

The participants from academia liked the Research Dive thanks to the networking and collaboration with government. Another positive aspect of the Research Dive shared by participants was that it enriched their understanding of statistics in terms of acknowledging different methodologies between lecturers and among universities. While doing the analysis, the academics offered unique perspectives according to their background, so the participants from BPS had the opportunity to reconnect with the capabilities of academia. The Research Dive involved BPS representatives from Central Java, West Papua, Nusa Tenggara, East Kalimantan and Jakarta, chosen through the competitive selection process, who appreciated the internal networking and collaboration opportunity as well.

Combining the Results into a Technical Report

Like the previous Research Dives, the five groups will write their findings in a paper. Pulse Lab Jakarta will combine all the papers into a technical report, which we will upload soon. You can stay up to date via the research dive microsite: www.rd.pulselabjakarta.id.

Pulse Lab Jakarta wishes to continue the collaboration with academia in Indonesia and to share the knowledge, methods and tools generated by these partnerships with decision-makers.